Public record
Software health reportschema 0.29.0 · metrics 2.10.0 · 2026-08-02 17:35 UTC

xrxbsx / goldmine

Goldmine, a new bot for Discord that keeps things nice and snug. Featuring VOICE (MUSIC), NATURAL LANGUAGE, IMAGES, CUSTOM WIDGETS, RANKS, and more!

PythonMIT★ 2 stars⑂ 5 forkssince Jan 2017View on GitHub ↗

xrxbsx/goldmine holds a health index of 3 out of 100, placing it in the Critical band. It scores highest on Community & Adoption (26/100) and lowest on Security (5/100). It was last updated 3482 days ago. A single contributor accounts for most of its recent work.

3
overall / 100
Critical

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

3
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 18 is calibrated to 13 on the published index scale (record calibration 2026-08-02). High-Risk Jurisdiction Policy applies a 20% multiplier to weighted overall health and gives it an At Risk ceiling of 34.

Ownership

xrxbsxPersonal account
2 followers43 public repossince Mar 2016

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIgoldminepoints to another repo — not scored0.0.0-0

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

20At Risk · 21% of overall
How it's scored
0/36Push recencylast push 3,482 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push3,482
active_weeks_last_year0
How it's scored
16.2/27Ships releases2 version tags (no GitHub releases)
0/36Release recencylatest release 3,520 days ago
27/27Release cadencea release every ~2.1 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count2
latest_release_tagv1.3.2-cogs
releases_from_tagsyes
days_since_latest_release3,520
mean_days_between_releases2.1
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

26At Risk · 17% of overall
How it's scored
0/60Stars2 stars
5/25Forks5 forks
0/15Watchers1 watchers
Inputs used
forks5
stars2
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

20At Risk · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0/22.5Commit distributiontop contributor authored 100% of commits
1.4/13.5Contributor breadth1 contributors
3/10OpenSSF Scorecard: Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1
How it's scored
0/42Issue resolutionno issues or no data
0/30PR acceptanceno decided pull requests or no data
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio
closed_unmerged_prs0
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, PR acceptance, Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
3.4/25Owner reach2 followers of xrxbsx
24/25Track record43 public repos, account ~10 yr old
Inputs used
followers2
owner_typeUser
is_verified
owner_loginxrxbsx
public_repos43
account_age_days3,804
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

21At Risk · 19% of overall
How it's scored
0/24CI workflows
0/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_cino
has_testsno
has_editorconfigno
has_linter_configno
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

5Critical · 16% of overall
How it's scored
6.8/7.5Binary-Artifactsbinaries present in source code
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Testsno data
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0.8/2.5Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
0/10Dangerous-Workflowno data
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesno data
0/5SASTno SAST tool detected
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsno data
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated12
scorecard_versionv5.5.0
checks_inconclusive6
scorecard_aggregate2.6
high_risk_jurisdiction_cap34
high_risk_jurisdiction_multiplier20
security_posture_after_multiplier5
security_posture_before_jurisdiction26
Excluded from scoring (no data or not applicable): CI-Tests, Dangerous-Workflow, Packaging, Pinned-Dependencies, Signed-Releases, Token-Permissions. Remaining weights renormalized. High-Risk Jurisdiction Policy applies a 20% multiplier and gives Security posture an At risk ceiling of 34.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

10Critical · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history0 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
0/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsno
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Pinned-Dependencies. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
54.4/55Manageable file sizes1/85 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes75,393
source_files_sampled85
oversized_source_files1

Key facts

2GitHub stars
1contributors
0commits, last 12 months
3,482days since last push
2releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'goldmine' points at a different repository (UNKNOWN); excluded from ecosystem scoring
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:goldmine@0.0.0; advisories assessed against the repository dependency graph instead

More detail

Star and fork history 0 ★ / 5 ⇿
0Stars
5Forks

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

12345512017-032018-062019-09

Each point covers 3 days.

OpenSSF Scorecard 2.6 / 10
2.6aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-08-02 17:35 UTC

9Binary-Artifactsbinaries present in source code
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
n/aPinned-Dependenciesno dependencies found
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
All dependencies not collected

The resolved dependency set could not be collected for this report: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.29.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.